264 lines
6.3 KiB
Matlab
264 lines
6.3 KiB
Matlab
function a = horzcat(varargin)
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%@info:
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%! @deftypefn {Function file} {@var{a} =} horzcat (@var{b},@var{c}, ...)
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%! @anchor{horzcat}
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%! @sp 1
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%! Method of the dynSeries class.
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%! @sp 1
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%! Merge Dynare time series objects. This method overloads the horizontal concatenation operator, so that
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%! two (or more) time series objects can be merged using the following syntax:
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%!
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%! a = [b, c, d];
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%! @sp 2
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%! @strong{Inputs}
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%! @sp 1
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%! @table @ @var
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%! @item b
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%! Dynare time series object, instantiated by @ref{dynSeries}.
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%! @item c
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%! Dynare time series object, instantiated by @ref{dynSeries}.
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%! @end table
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%! @sp 2
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%! @strong{Outputs}
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%! @sp 1
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%! @table @var
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%! @item a
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%! Dynare time series object.
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%! @end table
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%! @sp 2
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%! @strong{This function is called by:}
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%! @ref{descriptive_statistics}
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%!
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%! @strong{This function calls:}
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%! @ref{dynSeries}, @ref{private/horzcat2}
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%!
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%! @strong{Remark 1.} It is assumed that the two time series objects have the same frequencies. The two time series objects can cover
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%! different time ranges.
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%!
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%! @end deftypefn
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%@eod:
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% Copyright (C) 2011-2013 Dynare Team
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%
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% This file is part of Dynare.
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%
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% Dynare is free software: you can redistribute it and/or modify
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% it under the terms of the GNU General Public License as published by
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% the Free Software Foundation, either version 3 of the License, or
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% (at your option) any later version.
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%
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% Dynare is distributed in the hope that it will be useful,
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% but WITHOUT ANY WARRANTY; without even the implied warranty of
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% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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% GNU General Public License for more details.
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%
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% You should have received a copy of the GNU General Public License
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% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
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% Original author: stephane DOT adjemian AT univ DASH lemans DOT fr
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if nargin==0
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a = DynSeries();
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elseif nargin == 1
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a = varargin{1};
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elseif nargin==2
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a = horzcat2(varargin{1},varargin{2});
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else
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a = horzcat2(varargin{1},varargin{2});
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for i=3:nargin
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a = horzcat2(a,varargin{i});
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end
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end
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%@test:1
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%$ % Define a data set.
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%$ A = [transpose(1:10),2*transpose(1:10)];
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%$ B = [transpose(1:10),2*transpose(1:10)];
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%$
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%$ % Define names
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%$ A_name = {'A1';'A2'};
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%$ B_name = {'B1';'B2'};
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%$
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%$ % Define expected results.
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%$ e.time = dynDate(1);
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%$ e.freq = 1;
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%$ e.name = {'A1';'A2';'B1';'B2'};
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%$ e.data = [A,B];
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%$
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%$ % Instantiate two time series objects.
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%$ ts1 = dynSeries(A,[],A_name,[]);
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%$ ts2 = dynSeries(B,[],B_name,[]);
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%$
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%$ % Call the tested method.
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%$ ts3 = [ts1,ts2];
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%$
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%$ % Check the results.
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%$
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%$ t(1) = dyn_assert(ts3.init,e.time);
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%$ t(2) = dyn_assert(ts3.freq,e.freq);
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%$ t(3) = dyn_assert(ts3.data,e.data);
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%$ t(4) = dyn_assert(ts3.name,e.name);
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%$ T = all(t);
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%@eof:1
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%@test:2
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%$ % Define a data set.
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%$ A = [transpose(1:10),2*transpose(1:10)];
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%$ B = [transpose(5:12),2*transpose(5:12)];
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%$
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%$ % Define names
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%$ A_name = {'A1';'A2'};
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%$ B_name = {'B1';'B2'};
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%$
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%$ % Define initial date
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%$ A_init = 2001;
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%$ B_init = 2005;
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%$
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%$ % Define expected results.
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%$ e.time = [transpose(2000+(1:12)), ones(12,1)];
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%$ e.init = dynDate(2001);
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%$ e.freq = 1;
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%$ e.name = {'A1';'A2';'B1';'B2'};
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%$ e.data = [ [A; NaN(2,2)], [NaN(4,2); B]];
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%$
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%$ % Instantiate two time series objects.
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%$ ts1 = dynSeries(A,A_init,A_name,[]);
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%$ ts2 = dynSeries(B,B_init,B_name,[]);
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%$
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%$ % Call the tested method.
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%$ ts3 = [ts1,ts2];
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%$
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%$ % Check the results.
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%$ t(1) = dyn_assert(ts3.init,e.init);
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%$ t(2) = dyn_assert(ts3.freq,e.freq);
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%$ t(3) = dyn_assert(ts3.data,e.data);
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%$ t(4) = dyn_assert(ts3.name,e.name);
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%$ T = all(t);
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%@eof:2
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%@test:3
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%$ % Define a data set.
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%$ A = [transpose(1:7),2*transpose(1:7)];
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%$ B = [transpose(5:11),2*transpose(5:11)];
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%$
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%$ % Define names
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%$ A_name = {'A1';'A2'};
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%$ B_name = {'B1';'B2'};
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%$
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%$ % Define initial date
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%$ A_init = '1950Q1';
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%$ B_init = '1950Q3';
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%$
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%$ % Define expected results.
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%$ e.freq = 4;
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%$ e.init = dynDate('1950Q1');
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%$ e.name = {'A1';'A2';'B1';'B2'};
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%$ e.data = [ [A; NaN(2,2)], [NaN(2,2); B]];
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%$
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%$ % Instantiate two time series objects.
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%$ ts1 = dynSeries(A,A_init,A_name,[]);
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%$ ts2 = dynSeries(B,B_init,B_name,[]);
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%$
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%$ % Call the tested method.
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%$ ts3 = [ts1,ts2];
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%$
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%$ % Check the results.
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%$ t(1) = dyn_assert(ts3.init,e.init);
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%$ t(2) = dyn_assert(ts3.freq,e.freq);
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%$ t(3) = dyn_assert(ts3.data,e.data);
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%$ t(4) = dyn_assert(ts3.name,e.name);
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%$ T = all(t);
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%@eof:3
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%@test:4
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%$ % Define a data set.
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%$ A = [transpose(1:7),2*transpose(1:7)];
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%$ B = [transpose(5:9),2*transpose(5:9)];
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%$
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%$ % Define names
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%$ A_name = {'A1';'A2'};
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%$ B_name = {'B1';'B2'};
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%$
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%$ % Define initial date
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%$ A_init = '1950Q1';
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%$ B_init = '1950Q3';
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%$
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%$ % Define expected results.
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%$ e.init = dynDate(A_init);
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%$ e.freq = 4;
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%$ e.name = {'A1';'A2';'B1';'B2'};
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%$ e.data = [ A, [NaN(2,2); B]];
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%$
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%$ % Instantiate two time series objects.
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%$ ts1 = dynSeries(A,A_init,A_name,[]);
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%$ ts2 = dynSeries(B,B_init,B_name,[]);
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%$
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%$ % Call the tested method.
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%$ ts3 = [ts1,ts2];
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%$
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%$ % Check the results.
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%$ t(1) = dyn_assert(ts3.init,e.init);
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%$ t(2) = dyn_assert(ts3.freq,e.freq);
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%$ t(3) = dyn_assert(ts3.data,e.data);
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%$ t(4) = dyn_assert(ts3.name,e.name);
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%$ T = all(t);
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%@eof:4
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%@test:5
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%$ % Define a data set.
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%$ A = [transpose(1:10),2*transpose(1:10)];
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%$ B = [transpose(1:10),3*transpose(1:10)];
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%$ C = [transpose(1:10),4*transpose(1:10)];
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%$
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%$ % Define names
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%$ A_name = {'A1';'A2'};
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%$ B_name = {'B1';'B2'};
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%$ C_name = {'C1';'C2'};
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%$
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%$ % Define expected results.
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%$ e.init = dynDate(1);
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%$ e.freq = 1;
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%$ e.name = {'A1';'A2';'B1';'B2';'C1';'C2'};
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%$ e.data = [A,B,C];
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%$
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%$ % Instantiate two time series objects.
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%$ ts1 = dynSeries(A,[],A_name,[]);
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%$ ts2 = dynSeries(B,[],B_name,[]);
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%$ ts3 = dynSeries(C,[],C_name,[]);
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%$
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%$ % Call the tested method.
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%$ ts4 = [ts1,ts2,ts3];
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%$
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%$ % Check the results.
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%$ t(1) = dyn_assert(ts4.init,e.init);
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%$ t(2) = dyn_assert(ts4.freq,e.freq);
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%$ t(3) = dyn_assert(ts4.data,e.data);
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%$ t(4) = dyn_assert(ts4.name,e.name);
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%$ T = all(t);
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%@eof:5
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%@test:6
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%$ % Define a data set.
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%$ A = [transpose(1:10),2*transpose(1:10)];
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%$ B = [transpose(1:10),2*transpose(1:10)];
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%$
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%$ % Define names
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%$ A_name = {'A1';'A2'};
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%$ B_name = {'B1';'A2'};
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%$
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%$ % Instantiate two time series objects.
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%$ ts1 = dynSeries(A,[],A_name,[]);
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%$ ts2 = dynSeries(B,[],B_name,[]);
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%$
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%$ % Call the tested method.
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%$ try
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%$ ts3 = [ts1,ts2];
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%$ t = 0;
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%$ catch
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%$ t = 1;
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%$ end
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%$
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%$ T = t;
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%@eof:6
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